Minimum-necessary inputs
Define the smallest player and game context needed for each recommendation workflow rather than collecting data without a concrete purpose.
Trust by design
Social recommendations can affect player experience and opportunity. The platform must give studios clear boundaries, controls, and evidence for how those decisions are made.
Define the smallest player and game context needed for each recommendation workflow rather than collecting data without a concrete purpose.
Keep eligibility, blocking, reporting, and enforcement aligned with the game's authoritative systems and community standards.
Make the factors behind a recommendation available for evaluation, tuning, and governance.
Prefer pseudonymous, game-scoped identifiers over directly identifying player information.
Evaluate group stability and safety outcomes, not only whether an API produced a technically valid response.
Product and safety owners must remain able to review policy, investigate issues, and change or disable recommendation behavior.
Use only the behavioral data and parameters that a studio explicitly authorizes for the agreed purpose. Raw voice and chat are not required. Game-scoped observations should inform contextual teammate compatibility, not a universal personality or cross-studio reputation score.
Custom model training remains planned. Before using live player data, agree on training permissions, data retention and deletion, and any cloud processing. Participation in a technology program would not authorize sharing studio data. Learned recommendations must remain subject to studio-controlled eligibility, safety rules, evaluation, and rollback.
Production data flows, retention, deletion, access control, incident response, availability, and audit requirements will be agreed with design partners before live player data is used. This page states design direction, not a claim that a production compliance program has already been completed.
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